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318 results on '"de Boever, P."'

4. Pointwise visual field estimation from optical coherence tomography in glaucoma: a structure-function analysis using deep learning

Author

Hemelings, Ruben, Elen, Bart, Breda, João Barbosa, Bellon, Erwin, Blaschko, Matthew B, De Boever, Patrick, and Stalmans, Ingeborg

Subjects
Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Computer Vision and Pattern Recognition
Abstract

Background/Aims: Standard Automated Perimetry (SAP) is the gold standard to monitor visual field (VF) loss in glaucoma management, but is prone to intra-subject variability. We developed and validated a deep learning (DL) regression model that estimates pointwise and overall VF loss from unsegmented optical coherence tomography (OCT) scans. Methods: Eight DL regression models were trained with various retinal imaging modalities: circumpapillary OCT at 3.5mm, 4.1mm, 4.7mm diameter, and scanning laser ophthalmoscopy (SLO) en face images to estimate mean deviation (MD) and 52 threshold values. This retrospective study used data from patients who underwent a complete glaucoma examination, including a reliable Humphrey Field Analyzer (HFA) 24-2 SITA Standard VF exam and a SPECTRALIS OCT scan using the Glaucoma Module Premium Edition. Results: A total of 1378 matched OCT-VF pairs of 496 patients (863 eyes) were included for training and evaluation of the DL models. Average sample MD was -7.53dB (from -33.8dB to +2.0dB). For 52 VF threshold values estimation, the circumpapillary OCT scan with the largest radius (4.7mm) achieved the best performance among all individual models (Pearson r=0.77, 95% CI=[0.72-0.82]). For MD, prediction averaging of OCT-trained models (3.5mm, 4.1mm, 4.7mm) resulted in a Pearson r of 0.78 [0.73-0.83] on the validation set and comparable performance on the test set (Pearson r=0.79 [0.75-0.82]). Conclusion: DL on unsegmented OCT scans accurately predicts pointwise and mean deviation of 24-2 VF in glaucoma patients. Automated VF from unsegmented OCT could be a solution for patients unable to produce reliable perimetry results.

Published
2021

5. Deep learning on fundus images detects glaucoma beyond the optic disc

Author

Hemelings, Ruben, Elen, Bart, Barbosa-Breda, João, Blaschko, Matthew B., De Boever, Patrick, and Stalmans, Ingeborg

Subjects
Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Computer Vision and Pattern Recognition
Abstract

Although unprecedented sensitivity and specificity values are reported, recent glaucoma detection deep learning models lack in decision transparency. Here, we propose a methodology that advances explainable deep learning in the field of glaucoma detection and vertical cup-disc ratio (VCDR), an important risk factor. We trained and evaluated deep learning models using fundus images that underwent a certain cropping policy. We defined the crop radius as a percentage of image size, centered on the optic nerve head (ONH), with an equidistant spaced range from 10%-60% (ONH crop policy). The inverse of the cropping mask was also applied (periphery crop policy). Trained models using original images resulted in an area under the curve (AUC) of 0.94 [95% CI: 0.92-0.96] for glaucoma detection, and a coefficient of determination (R^2) equal to 77% [95% CI: 0.77-0.79] for VCDR estimation. Models that were trained on images with absence of the ONH are still able to obtain significant performance (0.88 [95% CI: 0.85-0.90] AUC for glaucoma detection and 37% [95% CI: 0.35-0.40] R^2 score for VCDR estimation in the most extreme setup of 60% ONH crop). Our findings provide the first irrefutable evidence that deep learning can detect glaucoma from fundus image regions outside the ONH.

Published
2021
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6. Pathological myopia classification with simultaneous lesion segmentation using deep learning

Author

Hemelings, Ruben, Elen, Bart, Blaschko, Matthew B., Jacob, Julie, Stalmans, Ingeborg, and De Boever, Patrick

Subjects
Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Computer Vision and Pattern Recognition
Abstract

This investigation reports on the results of convolutional neural networks developed for the recently introduced PathologicAL Myopia (PALM) dataset, which consists of 1200 fundus images. We propose a new Optic Nerve Head (ONH)-based prediction enhancement for the segmentation of atrophy and fovea. Models trained with 400 available training images achieved an AUC of 0.9867 for pathological myopia classification, and a Euclidean distance of 58.27 pixels on the fovea localization task, evaluated on a test set of 400 images. Dice and F1 metrics for semantic segmentation of lesions scored 0.9303 and 0.9869 on optic disc, 0.8001 and 0.9135 on retinal atrophy, and 0.8073 and 0.7059 on retinal detachment, respectively. Our work was acknowledged with an award in the context of the "PathologicAL Myopia detection from retinal images" challenge held during the IEEE International Symposium on Biomedical Imaging (April 2019). Considering that (pathological) myopia cases are often identified as false positives and negatives in classification systems for glaucoma, we envision that the current work could aid in future research to discriminate between glaucomatous and highly-myopic eyes, complemented by the localization and segmentation of landmarks such as fovea, optic disc and atrophy., Comment: 18 pages, 2 figures, preprint to journal

Published
2020

11. Combining epidemiological data and whole genome sequencing to understand SARS-CoV-2 transmission dynamics in a large tertiary care hospital during the first COVID-19 wave in The Netherlands focusing on healthcare workers

Author

Haanappel, Cynthia P., Oude Munnink, Bas B., Sikkema, Reina S., Voor in ’t holt, Anne F., de Jager, Herbert, de Boever, Rieneke, Koene, Heidy H. H. T., Boter, Marjan, Chestakova, Irina V., van der Linden, Anne, Molenkamp, Richard, Osbak, Kara K., Arcilla, Maris S., Vos, Margreet C., Koopmans, Marion P. G., and Severin, Juliëtte A.

Published
2023
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12. Cohort Profile: Pregnancy And Childhood Epigenetics (PACE) Consortium

Author

Felix, Janine F, Joubert, Bonnie R, Baccarelli, Andrea A, Sharp, Gemma C, Almqvist, Catarina, Annesi-Maesano, Isabella, Arshad, Hasan, Baïz, Nour, Bakermans-Kranenburg, Marian J, Bakulski, Kelly M, Binder, Elisabeth B, Bouchard, Luigi, Breton, Carrie V, Brunekreef, Bert, Brunst, Kelly J, Burchard, Esteban G, Bustamante, Mariona, Chatzi, Leda, Munthe-Kaas, Monica Cheng, Corpeleijn, Eva, Czamara, Darina, Dabelea, Dana, Smith, George Davey, De Boever, Patrick, Duijts, Liesbeth, Dwyer, Terence, Eng, Celeste, Eskenazi, Brenda, Everson, Todd M, Falahi, Fahimeh, Fallin, M Daniele, Farchi, Sara, Fernandez, Mariana F, Gao, Lu, Gaunt, Tom R, Ghantous, Akram, Gillman, Matthew W, Gonseth, Semira, Grote, Veit, Gruzieva, Olena, Håberg, Siri E, Herceg, Zdenko, Hivert, Marie-France, Holland, Nina, Holloway, John W, Hoyo, Cathrine, Hu, Donglei, Huang, Rae-Chi, Huen, Karen, Järvelin, Marjo-Riitta, Jima, Dereje D, Just, Allan C, Karagas, Margaret R, Karlsson, Robert, Karmaus, Wilfried, Kechris, Katerina J, Kere, Juha, Kogevinas, Manolis, Koletzko, Berthold, Koppelman, Gerard H, Küpers, Leanne K, Ladd-Acosta, Christine, Lahti, Jari, Lambrechts, Nathalie, Langie, Sabine AS, Lie, Rolv T, Liu, Andrew H, Magnus, Maria C, Magnus, Per, Maguire, Rachel L, Marsit, Carmen J, McArdle, Wendy, Melén, Erik, Melton, Phillip, Murphy, Susan K, Nawrot, Tim S, Nisticò, Lorenza, Nohr, Ellen A, Nordlund, Björn, Nystad, Wenche, Oh, Sam S, Oken, Emily, Page, Christian M, Perron, Patrice, Pershagen, Göran, Pizzi, Costanza, Plusquin, Michelle, Raikkonen, Katri, Reese, Sarah E, Reischl, Eva, Richiardi, Lorenzo, Ring, Susan, Roy, Ritu P, Rzehak, Peter, Schoeters, Greet, Schwartz, David A, Sebert, Sylvain, Snieder, Harold, Sørensen, Thorkild IA, and Starling, Anne P

Subjects
Epidemiology, Public Health, Health Sciences, Statistics, Mathematical Sciences, Child Health, Cohort Studies, DNA Methylation, Environmental Pollution, Epigenesis, Genetic, Female, Folic Acid, Humans, Infant, Newborn, Maternal Exposure, Maternal Health, Pregnancy, Prenatal Exposure Delayed Effects, Public Health and Health Services, Public health
Published
2018

17. Combination of snapshot hyperspectral retinal imaging and optical coherence tomography to identify Alzheimer’s disease patients

Author

Lemmens, Sophie, Van Craenendonck, Toon, Van Eijgen, Jan, De Groef, Lies, Bruffaerts, Rose, de Jesus, Danilo Andrade, Charle, Wouter, Jayapala, Murali, Sunaric-Mégevand, Gordana, Standaert, Arnout, Theunis, Jan, Van Keer, Karel, Vandenbulcke, Mathieu, Moons, Lieve, Vandenberghe, Rik, De Boever, Patrick, and Stalmans, Ingeborg

Published
2020
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19. Children’s microvascular traits and ambient air pollution exposure during pregnancy and early childhood: prospective evidence to elucidate the developmental origin of particle-induced disease

Author

Luyten, Leen J., Dockx, Yinthe, Provost, Eline B., Madhloum, Narjes, Sleurs, Hanne, Neven, Kristof Y., Janssen, Bram G., Bové, Hannelore, Debacq-Chainiaux, Florence, Gerrits, Nele, Lefebvre, Wouter, Plusquin, Michelle, Vanpoucke, Charlotte, De Boever, Patrick, and Nawrot, Tim S.

Published
2020
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24. Chemical-induced liver cancer: an adverse outcome pathway perspective

Author

Sanz-Serrano, Julen, Callewaert, Ellen, De Boever, Sybren, Drees, Annika, Verhoeven, Anouk, and Vinken, Mathieu

Abstract

ABSTRACTIntroductionThe evaluation of the potential carcinogenicity is a key consideration in the risk assessment of chemicals. Predictive toxicology is currently switching toward non-animal approaches that rely on the mechanistic understanding of toxicity.Areas coveredAdverse outcome pathways (AOPs) present toxicological processes, including chemical-induced carcinogenicity, in a visual and comprehensive manner, which serve as the conceptual backbone for the development of non-animal approaches eligible for hazard identification. The current review provides an overview of the available AOPs leading to liver cancer and discusses their use in advanced testing of liver carcinogenic chemicals. Moreover, the challenges related to their use in risk assessment are outlined, including the exploitation of available data, the need for semantic ontologies, and the development of quantitative AOPs.Expert OpinionTo exploit the potential of liver cancer AOPs in the field of risk assessment, 3 immediate prerequisites need to be fulfilled. These include developing human relevant AOPs for chemical-induced liver cancer, increasing the number of AOPs integrating quantitative toxicodynamic and toxicokinetic data, and developing a liver cancer AOP network. As AOPs and other areas in the field continue to evolve, liver cancer AOPs will progress into a reliable and robust tool serving future risk assessment and management.

Published
2024
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29. Scenes of Aesthetic Education: Ranciere, Oedipus, and 'Notre Musique'

Author

De Boever, Arne

Abstract

In an interview titled "The Janus-Face of Politicized Art," Jacques Ranciere describes his methodology as follows: "I always try to think in terms of horizontal distributions, combinations between systems of possibilities, not in terms of surface and substratum. Where one searches for the hidden beneath the apparent, a position of mastery is established. I have tried to conceive of a topography that does not presuppose this position of mastery." The aim is to construct "little by little, an egalitarian or anarchist theoretical position that does not presuppose this vertical relationship of top to bottom." In this essay, I ask, first, how we can theorize the two methodologies that Ranciere opposes in view of actual practices of aesthetic education. To further this theoretical reflection, I continue with some reflections on a graduate student seminar on aesthetics and politics that I taught in the Master's Program in Aesthetics and Politics in the School of Critical Studies at the California Institute of the Arts. Ranciere's work was one of the main inspirations for this program, and I reflect in this essay on how the methodology of horizontal distributions is played out in the aesthetic education that the program offers. In the third and fourth parts of this essay, I explore the ways in which these different methodologies circulate in what I am calling in my title two "scenes of aesthetic education": the first is Oedipus's confrontation with the Sphinx in Sophocles's famous play; the second is Jean-Luc Godard's discussion of the shot reverse shot film technique in his film Notre Musique. Each of these scenes enables one to understand much about Ranciere's methodology and its importance for aesthetic education. (Contains 38 notes.)

Published
2012

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